# How to Make AI Agents Accurate: Stop Treating Memory Like Chat History

Source: https://dinand.com/publications/agent-memory-and-state/
Author: Dinand Tinholt
Published: 2025-12-17

> A practical approach to keeping an agent’s constraints and current decisions clear during long sessions.

Article overview

This piece proposes managing explicit project state as a way to reduce drift in long-running agent sessions. It describes compact records of architectural decisions, constraints and current work, with periodic snapshots and resets. It also examines the risks of stale records and overly rigid rules. The article presents a working practice for building with agents.

[Read the full article on Medium ](https://medium.com/@tinholt/how-to-make-ai-agents-accurate-stop-treating-memory-like-chat-history-40eb8e0ea437)

This page is a short editorial overview. The original publication contains the complete article and any later updates.

Continue the thread

## A next room to enter.

[Choose another path ](https://dinand.com/)

[Medium · 2025

### The Next Frontier of Agentic AI: Context That Learns

How feedback from an agent’s work can inform the context it uses on the next task.

](https://dinand.com/publications/context-that-learns/)[LinkedIn · 2025

### GPT-5’s Multimodal Breakthrough: How AI Just Crossed the Expert Threshold in Business Reasoning

A business perspective on research combining visual information with complex written evidence.

](https://dinand.com/publications/multimodal-business-reasoning/)[Medium · 2025

### The AI Capability Overhang: Why the Most Powerful Technology Isn’t Working (yet)

Why organizations need to develop the operating capacity to use the AI capabilities already available.

](https://dinand.com/publications/ai-capability-overhang/)

[All publications ](https://dinand.com/publications/)[Essays ](https://dinand.com/essays/)

---
Site guide for AI agents: https://dinand.com/llms.txt
